AI Solution Architect

Hiring: AI Solution Architect

Client Name**: Corover.ai**

Immediate Joiners Preferred

Educational Qualification

• B.Tech./M.Tech./M.S./Ph.D. in Computer Science, IT, AI, or a related technical field.

Mandatory Experience

• Minimum 8–12 years of overall professional experience.
• At least 4–5 years in enterprise AI/ML solution architecture or large-scale data systems.
• Experience designing and deploying multi-component AI solutions in enterprise or government environments.

Mandatory Technical Skills

• Architecture: Microservices, serverless architecture, event-driven and domain-driven design, data architecture, and model lifecycle architecture.
• Cloud: AWS Bedrock, SageMaker, Lambda, API Gateway, S3; Azure OpenAI Service, Azure ML Studio, AKS; GCP Vertex AI, BigQuery, Cloud Storage.
• AI frameworks: TensorFlow, PyTorch, Hugging Face Transformers, LangChain, LLM orchestration, prompt engineering, and Responsible AI.
• Data and storage: SQL, PostgreSQL, MySQL, MongoDB, DynamoDB, Pinecone, and Weaviate.
• Integration: REST APIs, GraphQL, WebSocket, enterprise integration, and interoperability frameworks.
• Conversational AI: Speech-to-Text, Text-to-Speech, chatbot pipelines, RAG, vector stores, and LLM integration.
• Security: IAM, RBAC, encryption at rest and in transit, data privacy, and AI governance.

Key Responsibilities

• Design end-to-end AI/ML solution architectures and integrations with enterprise and government platforms.
• Define APIs, interoperability standards, data flows, security, scalability, and deployment architecture.
• Evaluate cloud-native and on-premises deployment models.
• Lead architecture reviews, technical governance, and mentoring of engineering teams.

Preferred: AWS/Azure/GCP architecture certifications, research papers, case studies, and open-source contributions.

Pay: ₹2,200,000.00 - ₹4,200,000.00 per year

Application Question(s):

• What is your highest educational qualification?
• How many years of total professional experience do you have?
• How many years of experience do you have in enterprise AI/ML solution architecture or large-scale data systems?
• Have you designed and deployed multi-component AI solutions in enterprise or government environments?
• Which cloud AI platforms have you worked with hands-on?
• Do you have experience designing microservices, serverless, event-driven, and domain-driven architectures?
• Have you implemented LLM-based solutions using RAG, vector databases, and LLM orchestration frameworks such as LangChain?
• Which AI/ML frameworks have you used professionally?
• Do you have experience designing secure AI systems with IAM/RBAC, encryption, data privacy, and AI governance?
• Have you led architecture reviews, defined enterprise integrations/APIs, and mentored engineering teams?
• Do you hold AWS, Azure, or GCP architecture certifications, or have relevant research papers/open-source contributions?
• How soon you can join

Work Location: In person